Experience

Aug 2022 - Present AI Data Engineer at Riley

– Successfully let led the implementation and migration of
the comprehensive data warehouse solution for NBL on the
GCP, encompassing five different platform data pipelines.
– Created the seamless extraction, transformation and
integration of diverse datasets resulting in improved data
accuracy and accessibility for business insights,
– Collaborated closely with cross-functional teams, including
data engineers, analysts, and stakeholders, to define
project requirements, establish data governance practices,
and design effective data pipelines.
– Stan x Google (Recommendation AI model with Discovery
Engine):
– Collaborated closely with the Google team on a project with
Stan, a streaming platform, to enhance the Discovery
engine’s recommendation system. Leveraged users’ watch
history and program data to pre-process and prepare the
data for feeding into the recommendation model, resulting
in more personalised and accurate program recommendations
for users.
– Led the fine-tuning efforts of the recommendation model to
enhance the accuracy and effectiveness of program
recommendations for Stan’s users. Employed advanced
techniques to refine the program data, incorporating
additional parameters and features to enrich the data fed
into the model, resulting in improved recommendation
precision and user satisfaction.
– Worked collaboratively with stakeholders from Stan and the
Google team, including data scientists and engineers, to
define project requirements, ensure data quality, and
iterate on the recommendation model. Effectively
communicated insights and findings to both technical and
non-technical stakeholders, driving informed decision-
making and contributing to the success of the project.
– Spearheaded a logs summarisation project utilising Gemini
AI to streamline error analysis and reporting.
– Designed and implemented a logs summarisation model using
GCP logs data as input, providing detailed error solutions
and causes in CSV format.
– Automated the generation of error summary reports,
identifying major errors and pinpointing areas of concern
across different environments and resources.
– Significantly reduced monitoring time and improved
efficiency in troubleshooting by consolidating and
analysing logs effectively.

June 2021 - Sept 2022 Data Engineer at Advice Intelligence

– Fin-tech start-up that have one of kind financial planning
software, where I am responsible to end-to-end migration of
client’s data which includes the operation of extract,
transform and load on our platform.
– As a data migration engineer, I extract all the data from
various sources using SQL Server Management Studio and load
it to specific data environment using SSIS packages and
PostgreSQL functions where I perform data transforming and
mapping of financial products, financial platforms,
insurances, and many more using PostgreSQL in Dbeaver,
which goes through detailed review in ETL environment, I
load the data to PROD environment once confirmed by the
client.
– I am also responsible for maintaining and enhancing the ETL
pipelines using SSIS packages, perform analysis in
PostgreSQL for support desk issues and making new SSIS
packages and PostgreSQL functions for excel data sources

Feb 2020 - May 2020 Customer insight Analyst at Quantium

– Virtual experience where Conducted analysis on client’s
transaction dataset and identify customer purchasing
behaviour to generate insight and provide commercial
recommendations using R and tableau.
– Moreover, test that analysis on the trial store and prepare
the final report about customer behaviour insight

July 2020 - Oct 2020 Data Analyst at ANZ bank

– Short term virtual internship where I Forecasted
transaction patterns & strategise business plans for high
revenue turnover via data modelling & analysis by R.
Prepared in detailed data insights dashboards using
tableau.
– Assessed transaction data of 27K bank customers of last 3
months to prepare tableau dashboard & draft insight report